library(fixest);library(AER);library(stringr)
rm(list=setdiff(ls(), "twd")) 
options(warn=-1)



data<-readRDS(paste(twd,"data/made_data/vreg_wgeos_race.rds",sep=""))


## In person 20
data$in_person_primary_20<-ifelse(data$voting_method_200303 == "P",1,0)
## Abs early 20
data$abs_early_primary_20<-ifelse(data$voting_method_200303 %in% c("A","E"),1,0)
## In person 18
data$in_person_general_18<-ifelse(data$voting_method_181106 == "P",1,0)
## Abs early 18
data$abs_early_general_18<-ifelse(data$voting_method_181106 %in% c("A","E"),1,0)
## Take First Difference
data$diff_in_person<-data$in_person_primary_20-data$in_person_general_18
data$diff_abs_early<-data$abs_early_primary_20-data$abs_early_general_18
### get the minimum of the distance to a consolidated (including super sites)
data$distance_realized_min<-apply(cbind(data$distance_realized,data$distancegov1,data$distancegov2),1,min,na.rm=T)
## Difference between assigned and realized distances (in logs and levels)
data$ln_dist_change<-ifelse(data$moved==1,log(data$distance_realized_min)-log(data$distance_assigned),0)
data$lev_dist_change<-ifelse(data$moved==1,data$distance_realized_min-data$distance_assigned,0)
### Difference between assigned and realized size # of assigned voters (in logs and levels)
data$ln_diff_N<-log(data$realized_N)-log(data$assigned_N)
data$lev_diff_N<-data$realized_N-data$assigned_N

#### Create differences in turnout for all previous elections and run regression ######

## 18-18b

data$in_person_primary_18<-ifelse(data$voting_method_180802== "P",1,0)
data$abs_early_primary_18<-ifelse(data$voting_method_180802 %in% c("A","E"),1,0)

data$diff_in_person_18_18<-data$in_person_general_18-data$in_person_primary_18
data$diff_abs_early_18_18<-data$abs_early_general_18-data$abs_early_primary_18

## 18-16

data$in_person_general_16<-ifelse(data$voting_method_161108== "P",1,0)
data$abs_early_general_16<-ifelse(data$voting_method_161108 %in% c("A","E"),1,0)

data$diff_in_person_18_16<-data$in_person_primary_18-data$in_person_general_16
data$diff_abs_early_18_16<-data$abs_early_primary_18-data$abs_early_general_16

## 16-16a

data$in_person_primary_16a<-ifelse(data$voting_method_160804== "P",1,0)
data$abs_early_primary_16a<-ifelse(data$voting_method_160804 %in% c("A","E"),1,0)

data$diff_in_person_16_16a<-data$in_person_general_16-data$in_person_primary_16a
data$diff_abs_early_16_16a<-data$abs_early_general_16-data$abs_early_primary_16a

## 16a-16b

data$in_person_primary_16b<-ifelse(data$voting_method_160301== "P",1,0)
data$abs_early_primary_16b<-ifelse(data$voting_method_160301 %in% c("A","E"),1,0)


data$diff_in_person_16_16b<-data$in_person_primary_16a-data$in_person_primary_16b
data$diff_abs_early_16_16b<-data$in_person_primary_16a-data$abs_early_primary_16b

## 16b-14

data$in_person_general_14<-ifelse(data$voting_method_141104== "P",1,0)
data$abs_early_general_14<-ifelse(data$voting_method_141104 %in% c("A","E"),1,0)

data$diff_in_person_16_14<-data$in_person_primary_16b-data$in_person_general_14
data$diff_abs_early_16_14<-data$in_person_primary_16b-data$abs_early_general_14

## 14-14a

data$in_person_primary_14<-ifelse(data$voting_method_140807== "P",1,0)
data$abs_early_primary_14<-ifelse(data$voting_method_140807 %in% c("A","E"),1,0)

data$diff_in_person_14_14<-data$in_person_general_14 - data$in_person_primary_14
data$diff_abs_early_14_14<-data$abs_early_general_14 - data$abs_early_primary_14

## 14a-12

data$in_person_general_12<-ifelse(data$voting_method_121106== "P",1,0)
data$abs_early_general_12<-ifelse(data$voting_method_121106 %in% c("A","E"),1,0)

data$diff_in_person_14_12<-data$in_person_primary_14 - data$in_person_general_12
data$diff_abs_early_14_12<-data$abs_early_primary_14 - data$abs_early_general_12



### Length of unique ops
lu<-function(x){length(unique(x))}


## Get  Dem votes
dem_votes<-function(x){ 
  sum( ifelse(str_trim(x) %in% c("DG","D"),1,0 ))
}

## Get  Rep votes
rep_votes<-function(x){ 
  sum( ifelse(str_trim(x) %in% c("RG","R"),1,0 ))
}

## Get All votes
total_votes<-function(x){
  sum(x)
}

## Get Dem/Rep Votes for each
data$dem_primary_votes<-apply(data[,c("party_voted_180802","party_voted_160804", "party_voted_160301","party_voted_140807")],1, dem_votes)
data$rep_primary_votes<-apply(data[,c("party_voted_180802","party_voted_160804", "party_voted_160301","party_voted_140807")],1, rep_votes)

## Absentee 
votes_abs<-c("abs_early_primary_18","abs_early_general_16","abs_early_primary_16a","abs_early_primary_16b","abs_early_general_14","abs_early_primary_14","abs_early_general_12")
## In Person
votes_in<-c("in_person_primary_18","in_person_general_16","in_person_primary_16a","in_person_primary_16b","in_person_general_14","in_person_primary_14","in_person_general_12")
## Absentee | Primary
primary_abs<-c("abs_early_primary_18","abs_early_primary_16a","abs_early_primary_16b","abs_early_primary_14")
## In Person | Primary
primary_in<-c("in_person_primary_18","in_person_primary_16a","in_person_primary_16b","in_person_primary_14")

### Get each of these for the individual
data$all_votes<-apply(data[,c(votes_abs,votes_in)],1, total_votes)
data$primary_votes<-apply(data[,c(primary_abs,primary_in)],1, total_votes)
data$general_votes<-data$all_votes- data$primary_votes


### Run Regressions

suppressMessages({

ft1<-feols(diff_in_person~(moved+consolidated)*all_votes+I(dist_damage_min<500)+I(dist_power_min<500)+diff_abs_early|
                     all_votes,data=data,cluster~polling_place_text_name,warn=F)
ft2<-feols(diff_in_person~(moved+consolidated)*general_votes+I(dist_damage_min<500)+I(dist_power_min<500)+diff_abs_early|
                     general_votes,data=data,cluster~polling_place_text_name,warn=F)
ft3<-feols(diff_in_person~(moved+consolidated)*primary_votes+I(dist_damage_min<500)+I(dist_power_min<500)+diff_abs_early|
                     primary_votes,data=data,cluster~polling_place_text_name,warn=F)
ft4<-feols(diff_in_person~(moved+consolidated)*(dem_primary_votes+rep_primary_votes)+I(dist_damage_min<500)+I(dist_power_min<500)+diff_abs_early|
                     dem_primary_votes+rep_primary_votes,data=data,cluster~polling_place_text_name,warn=F)
})
## F-stats for dem,rep equality of effects


Fc1<-linearHypothesis(ft4, "moved:dem_primary_votes = moved:rep_primary_votes", test="F", cluster=~polling_place_text_name)
Fc2<-linearHypothesis(ft4, "consolidated:dem_primary_votes = consolidated:rep_primary_votes", test="F", cluster=~polling_place_text_name)



log_print(
  esttex(ft1,ft2,ft3,ft4,coefstat = "confint",signif.code = NA, 
       keep = c("moved","consolidated","moved:all_votes", "all_votes:consolidated",
                "moved:primary_votes", "consolidated:primary_votes",
                "moved:dem_primary_votes","moved:rep_primary_votes",
                "consolidated:dem_primary_votes", "consolidated:rep_primary_votes",
                "moved:general_votes","general_votes:consolidated"), fitstat = c("n")
       )
  )

log_print(rbind(c(round(Fc1[[3]][2],4),"&",round(Fc2[[3]][2],4), "\\" ), 
      c(round(Fc1[[4]][2],4), "&",round(Fc2[[4]][2],4),"\\")
  ), row.names=F
)